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Systematic Error: Methodological and Sampling Errors01:15

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In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
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Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
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Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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Implementation errors in the GingerALE Software: Description and recommendations.

Simon B Eickhoff1,2, Angela R Laird3, P Mickle Fox4

  • 1Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Germany.

Human Brain Mapping
|August 12, 2016
PubMed
Summary
This summary is machine-generated.

Two errors in the GingerALE software, used for neuroimaging meta-analysis, have been identified. These errors led to more liberal statistical inferences in published studies, impacting replicability in neuroscience research.

Keywords:
cluster inferencefMRIfalse positivesmeta-analysisstatistics

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Computational Neuroscience

Background:

  • Neuroimaging analysis relies on sophisticated, freely distributed software.
  • Replicability of neuroimaging studies is a significant challenge.
  • Coordinate-based meta-analysis is crucial for consolidating neuroimaging findings.

Purpose of the Study:

  • To report two errors in the GingerALE software for coordinate-based meta-analysis.
  • To inform researchers using GingerALE about potential statistical inference issues.
  • To promote transparency and open error management in scientific software.

Main Methods:

  • Identification and verification of two distinct errors within the GingerALE software package.
  • Analysis of the impact of these errors on statistical inferences in published meta-analyses.
  • Review of the role of third-party software in scientific research.

Main Results:

  • Two errors were confirmed in GingerALE, a widely used neuroimaging meta-analysis tool.
  • These errors resulted in statistically more liberal inferences than intended by study authors.
  • Published studies using the affected GingerALE versions may have compromised statistical rigor.

Conclusions:

  • Researchers using GingerALE should be aware of these errors and consider re-analyses.
  • Transparency in reporting and managing software errors is vital for scientific integrity.
  • The reliance on third-party software necessitates careful validation and error checking in scientific research.